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Ladders of Thought: A Self-Evolving Curriculum of Progressively Simplified Reasoning Traces

arXiv:2609.25643v1 Announce Type: cross Abstract: Large language models (LLMs) excel at reasoning when scaled to hundreds of billions of parameters, but small- and mid-scale models remain brittle reas

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Latent Dataset Distillation for Human Motion Prediction

DGX agent

arXiv:2609.26430v1 Announce Type: new Abstract: Dataset distillation (DD) compresses a large training set into a compact synthetic set while preserving downstream training utility. Although DD has bee

researcharxiv-cs-cv

23 Sept 2026

Leaky-integrator reconstruction: taming error accumulation in recursive differenced time-series forecasting

arXiv:2609.23378v1 Announce Type: new Abstract: We introduce leaky-integrator reconstruction, a training-free method that cures the error accumulation of recursive differenced forecasting. Our first c

Learnable Classifier-Free Guidance Null Embeddings for Enhanced Controllable Speech Synthesis

arXiv:2609.25411v1 Announce Type: cross Abstract: Classifier-free Guidance (CFG) is widely adopted in text-to-speech (TTS) systems to enhance generation quality and conditioning fidelity by interpolat

Learning Neural Feedback Linearization for Data-driven Systems via Augmented Lagrangian

arXiv:2609.25163v1 Announce Type: new Abstract: The paper proposes a novel data-driven framework for designing and training a feedback linearizing controller by explicitly incorporating relative degre

LiFR v2: Completion-Augmented Event Propagation for High-Rate Dense Prediction

arXiv:2609.25803v2 Announce Type: new Abstract: High-rate dense perception in dynamic environments is limited by the low update rate of RGB cameras, as rapid scene changes can occur between frames. Ev

Linear probing enables Ship-Radiated Noise recognition with pretrained audio embeddings

arXiv:2601.08358v2 Announce Type: replace Abstract: Even though the ocean covers the majority of the planet's surface, it remains the least explored ecosystem. As light and radio waves do not propagat

Listen Then Reason: Perception-Grounded Test-Time Reinforcement Learning for Large Audio-Language Models

arXiv:2609.23589v1 Announce Type: cross Abstract: Large audio-language models (LALMs) are increasingly used for a broader range of audio reasoning tasks. These models typically incorporate audio repre

LLaVA-Assessor: Building the Foundation LMM For Visual Quality Assessment

arXiv:2609.26205v1 Announce Type: new Abstract: Aligning with the human visual system~(HVS) in perceiving and evaluating the quality of visual signals is a central objective of machine-vision-based vi

LLM next-token prediction is already a probabilistic classifier, so an open LLM can serve a Jev-like interface: discrete options in, fast pr…

researchsoumith-chintala--x

LLM next-token prediction is already a probabilistic classifier, so an open LLM can serve a Jev-like interface: discrete options in, fast probabilities out. Our own @ekzhang1 made it better at the job

Longitudinal Retinal Vascular Remodeling in Myopic Children Treated with Orthokeratology or Defocus Lenses: A Two-Year Comparative Study

arXiv:2609.26662v1 Announce Type: new Abstract: Purposes: To characterize longitudinal retinal vascular changes in myopic children treated with orthokeratology (OK) or multifocal defocus lenses (Defoc

Low-Rank Attention Residuals

arXiv:2607.09694v2 Announce Type: replace-cross Abstract: Attention Residuals (AttnRes) replace the fixed residual sum with depth-wise attention over previous sub-layer outputs in Large Language Model

Mammo-LIFE: Longitudinal Mammographic Imaging and Clinical Feature Enrichment for Post-Radiotherapy Outcome Prediction

arXiv:2609.26443v1 Announce Type: new Abstract: Recent advances in Artificial Intelligence (AI)-powered Computer-Aided Diagnosis (CAD) systems have substantially improved breast cancer screening, diag

Manipulation of Deformable Linear Objects Using Model Predictive Path Integral Control with Bidirectional Long Short-Term Memory Learning

arXiv:2609.26238v1 Announce Type: new Abstract: The manipulation of Deformable Linear Objects (DLOs) such as cables poses a significant challenge for automation due to their infinite degrees of freedo

Manipulation with Stability Guarantees: Linear Deformable Objects with Non-negligible Physical Response Grasped at Multiple Location

arXiv:2609.26004v1 Announce Type: new Abstract: Most research on the manipulation of deformable objects focuses on lightweight systems with negligible mechanical response, effectively restricting atte

Margin-Drop Coordinates for Cross-Budget Robustness Evaluation

arXiv:2609.26081v1 Announce Type: new Abstract: Fixed-budget robustness evaluation can select the wrong frozen vision encoder. An encoder that survives a shallow attack may lose most of that robustnes

mbariml: a curation pipeline for turning deep-sea imagery and video into object-detection training data

arXiv:2609.25500v1 Announce Type: new Abstract: Training data quantity and quality greatly affect object detection model performance, regardless of model architecture. When using object detection mode

Mean Velocity Matching: Rethinking Generative Dynamics in Diffusion Models

arXiv:2609.25444v1 Announce Type: new Abstract: This work studies prediction parameterization for stochastic generative dynamics in diffusion models. Existing velocity-based generative models provide

MECT: Mixture of Experts with CNN-Transformer Network for Speaker verification

arXiv:2609.24061v1 Announce Type: cross Abstract: In this paper, we propose MECT, a speaker verification model that integrates the Mixture-of-Experts (MoE) mechanism into a CNN-Transformer backbone wi

MemoryAthena: Adaptive Routing over Latent and Generated Memories

arXiv:2609.25853v1 Announce Type: new Abstract: Learned-memory methods store information in an explicit table and consume it through a separate reader, allowing addressing, storage, and reading to be

MIAR: Medical Image Super-Resolution With Autoregressive Modeling

arXiv:2609.26103v1 Announce Type: new Abstract: Medical Image Super-Resolution (MISR) aims to enhance spatial resolution without requiring hardware modifications. Although deep learning has yielded pr

MICRO: Multi-Fidelity Active Search for Severe Error Discovery

arXiv:2609.26025v1 Announce Type: cross Abstract: Human feedback can vary in cost and informativeness. Strong feedback can reveal severe errors but is costly, so cheaper quality ratings can help decid

MIND the Gap: A Geographic Implicit Neural Representation with Adjustable Spatial Scale

arXiv:2609.25454v1 Announce Type: cross Abstract: Geographic measurements are often sparse, leaving large areas without labels for the quantities we want to map. Geographic implicit neural representat

Mitigating Sequential Reappearance in Diffusion Data-Point Unlearning

arXiv:2609.25166v1 Announce Type: new Abstract: Diffusion data-point unlearning is typically evaluated immediately after each deletion, even though subsequent requests may repeatedly update the same m

Mode Collapse Is Cheap to Detect: A Ground-Truth-Free Pre-Flight Check for Neural Samplers

arXiv:2609.26272v1 Announce Type: new Abstract: Neural samplers are trained against an unnormalised target ildepi=e^{-E} with no samples from pi, which leaves the practitioner with no way to tell whet

MT-ProtBERT: Multi-task Learning ProtBERT for Intrinsically Disordered Proteins Classification with Scarce Data

arXiv:2609.25334v1 Announce Type: new Abstract: Intrinsically disordered proteins (IDPs) differ from folded proteins in that they are dynamic, lack a stable three-dimensional conformation, and have lo

Multi-Axis Selective Decoupling Framework for Free-Floating Space Manipulators

arXiv:2609.26267v1 Announce Type: new Abstract: Free-floating space manipulator systems face operational challenges due to dynamic coupling. While traditional reactionless manipulation eliminates base

Multi-Term Fourier Graph Neural Network with Sample Relationship Learning for Enhanced Remaining Useful Life Prediction

arXiv:2609.25179v1 Announce Type: new Abstract: Predicting the remaining useful life (RUL) is essential for effective predictive maintenance. Spatio-Temporal Graph Neural Networks (ST-GNNs), which can

NAWE: Digital Watermarking with Neural-Assisted Watermark Extraction

arXiv:2609.25972v1 Announce Type: new Abstract: NAWE (Neural-Assisted Watermark Extraction) combines an explicit signal-processing watermarking construction with a pretrained neural host predictor. A

Neighbor-Aware Token Reduction via Hilbert Curve for Vision Transformers

arXiv:2512.22760v2 Announce Type: replace Abstract: Vision Transformers (ViTs) have achieved remarkable success in visual recognition tasks, but redundant token representations limit their computation

Neoadjuvant chemotherapy response prediction using pretreatment diffusion and contrast-enhanced magnetic resonance imaging with clinical variables

arXiv:2609.26105v1 Announce Type: cross Abstract: Prediction of pathological complete response before neoadjuvant chemotherapy may facilitate more tailored therapeutic planning for breast cancer patie

Neural Approximation by Function Composition: Rigidity and Doubly Exponential Convergence

arXiv:2609.25874v1 Announce Type: new Abstract: Deep neural networks approximate functions by composing affine maps with nonlinear activations, but how composition itself creates approximation power i

Notes on Fourier-Bessel wavelets

arXiv:2609.26537v1 Announce Type: new Abstract: These notes develop the mathematical foundations and construction of a Fourier-Bessel wavelet family inspired by the disk harmonics of Shaqfa et al.[9].

NPU Accelerator: Quantized Real-Time Vehicle Detection on PYNQ-Z1 Using FINN

arXiv:2609.24757v1 Announce Type: cross Abstract: This paper presents the design, optimization, implementation, and on-board validation of a neural processing unit (NPU) accelerator for real-time vehi

Observed Control - Linearly Scalable Nonlinear Model Predictive Control with Adaptive Horizons

arXiv:2508.13339v2 Announce Type: replace-cross Abstract: This work highlights the duality between state estimation and model predictive control. A model predictive controller, observed control, is pr

Observer Choice and Threshold Selection in Retinal Vessel Segmentation: A Subject-Separated Evaluation

arXiv:2609.25597v1 Announce Type: new Abstract: The annotation used to select a segmentation threshold is part of the evaluation protocol, yet its effect is easily conflated with model quality. We exa

On Basis Function Selection for Sparse Gaussian Process Regression

arXiv:2609.26624v1 Announce Type: cross Abstract: Sparse Gaussian processes achieve O(N) inference by replacing the kernel with an appropriate expansion in a fixed basis {phi_j} on the input space. Gi

On Probabilistic Inference Through Parametric Tensor Decomposition in Base Tensor Networks

arXiv:2609.23774v1 Announce Type: new Abstract: Probabilistic inference is generally only tractable in low-treewidth graphical models, limiting its effective applicability in high-treewidth settings.

On the Gradient Heterogeneity Dynamics of Adversarially Robust Federated Regression

arXiv:2609.25705v1 Announce Type: cross Abstract: Federated learning (FL) is intrinsically heterogeneous: honest clients may have different data-generating models. On top of that, adversarial clients

On the Lexical Superstition of Large Language Models for Code Comprehension: Re-evaluation on Code of Low Lexical Quality

arXiv:2609.26388v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have made them widely used for code-related tasks. Identifier names are statistically informative in n

On the Role of the Projector in Contrastive Self-Supervised Learning: Last-Layer Rank Dynamics Drive Representation Quality

arXiv:2609.26334v1 Announce Type: new Abstract: The dimensional collapse of representations in self-supervised contrastive learning is an ever-present issue. One notable technique to prevent such a co

One Domain, Many Tongues: Composing Domain and Language LoRAs for Cross-Lingual Remote-Sensing MLLMs without Paired Data

arXiv:2609.26097v1 Announce Type: new Abstract: Remote-sensing (RS) multimodal large language models (MLLMs) are trained and evaluated only in English, while text-only instruction data covers over 100

One-Step Generative Surrogate Models via Block-Triangular Joint Drifting

arXiv:2609.26435v1 Announce Type: new Abstract: Drifting provides a direct route to one-step generative models, but applying it directly to stochastic transition modeling requires multiple samples of

PACE-dLLM: Elastic Block Decoding via Confidence Cliff Estimation for Diffusion Language Models

arXiv:2609.26249v1 Announce Type: new Abstract: Diffusion language models (dLLMs), such as LLaDA and Dream, have become competitive with autoregressive (AR) LLMs in generation quality while supporting

PARTE: Plane-Assisted Robust Transformation Estimation for Point Cloud Registration

arXiv:2609.25375v1 Announce Type: new Abstract: Global point-cloud registration remains challenging when limited overlap, repetitive geometry, and sensor noise produce correspondence sets dominated by

Partially Observed Sparse Graphs: The Unknown Sampling Rate is a Tail Index

arXiv:2609.26199v1 Announce Type: new Abstract: A large graph is often available only in part: a crawl stopped by its budget, a panel, a partial dump. When the sampled fraction s is known by design th

PartLLM: A Unified Multimodal Foundation for 3D Part Segmentation

arXiv:2609.25832v1 Announce Type: new Abstract: Part segmentation is a fundamental problem in computer graphics and 3D vision. Recent works have expanded 3D part segmentation beyond fixed taxonomies,

PermuFormer: Multi-Task Pretraining for Permutation Representation in Algebraic Combinatorics

arXiv:2609.25438v1 Announce Type: new Abstract: Diverse pretraining has been shown to be an effective method for learning reusable, domain-aware representations that provide a starting point for fine-